Liver metastases: Microenvironments and ex-vivo models

肝转移瘤:微环境和离体模型

阅读:1

Abstract

The liver is a highly metastasis-permissive organ, tumor seeding of which usually portends mortality. Its unique and diverse architectural and cellular composition enable the liver to undertake numerous specialized functions, however, this distinctive biology, notably its hemodynamic features and unique microenvironment, renders the liver intrinsically hospitable to disseminated tumor cells. The particular focus for this perspective is the bidirectional interactions between the disseminated tumor cells and the unique resident cell populations of the liver; notably, parenchymal hepatocytes and non-parenchymal liver sinusoidal endothelial, Kupffer, and hepatic stellate cells. Understanding the early steps in the metastatic seeding, including the decision to undergo dormancy versus outgrowth, has been difficult to study in 2D culture systems and animals due to numerous limitations. In response, tissue-engineered biomimetic systems have emerged. At the cutting-edge of these developments are ex vivo 'microphysiological systems' (MPS) which are cellular constructs designed to faithfully recapitulate the structure and function of a human organ or organ regions on a milli- to micro-scale level and can be made all human to maintain species-specific interactions. Hepatic MPSs are particularly attractive for studying metastases as in addition to the liver being a main site of metastatic seeding, it is also the principal site of drug metabolism and therapy-limiting toxicities. Thus, using these hepatic MPSs will enable not only an enhanced understanding of the fundamental aspects of metastasis but also allow for therapeutic agents to be fully studied for efficacy while also monitoring pharmacologic aspects and predicting toxicities. The review discusses some of the hepatic MPS models currently available and although only one MPS has been validated to relevantly modeling metastasis, it is anticipated that the adaptation of the other hepatic models to include tumors will not be long in coming.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。